1 code implementation • CVPR 2020 • Haotian Yang, Hao Zhu, Yanru Wang, Mingkai Huang, Qiu Shen, Ruigang Yang, Xun Cao
In this paper, we present a large-scale detailed 3D face dataset, FaceScape, and propose a novel algorithm that is able to predict elaborate riggable 3D face models from a single image input.
1 code implementation • 1 Nov 2021 • Hao Zhu, Haotian Yang, Longwei Guo, Yidi Zhang, Yanru Wang, Mingkai Huang, Menghua Wu, Qiu Shen, Ruigang Yang, Xun Cao
By training on FaceScape data, a novel algorithm is proposed to predict elaborate riggable 3D face models from a single image input.
1 code implementation • 4 Jan 2022 • Yunze Xiao, Hao Zhu, Haotian Yang, Zhengyu Diao, Xiangju Lu, Xun Cao
By fitting a 3D morphable model from multi-view images, the features of multiple images are extracted and aggregated in the mesh-attached UV space, which makes the implicit function more effective in recovering detailed facial shape.
no code implementations • 6 Aug 2021 • Hao Zhu, Xinxin Zuo, Haotian Yang, Sen Wang, Xun Cao, Ruigang Yang
In this paper, we propose a novel learning-based framework that combines the robustness of the parametric model with the flexibility of free-form 3D deformation.
no code implementations • 8 Sep 2023 • Haotian Yang, Mingwu Zheng, Wanquan Feng, Haibin Huang, Yu-Kun Lai, Pengfei Wan, Zhongyuan Wang, Chongyang Ma
Specifically, TRAvatar is trained with dynamic image sequences captured in a Light Stage under varying lighting conditions, enabling realistic relighting and real-time animation for avatars in diverse scenes.
no code implementations • 6 Feb 2024 • Haotian Yang, Mingwu Zheng, Chongyang Ma, Yu-Kun Lai, Pengfei Wan, Haibin Huang
In this paper, we introduce the Volumetric Relightable Morphable Model (VRMM), a novel volumetric and parametric facial prior for 3D face modeling.
no code implementations • 15 Apr 2024 • Chi Wang, Junming Huang, Rong Zhang, Qi Wang, Haotian Yang, Haibin Huang, Chongyang Ma, Weiwei Xu
SDS boosts GANs with more generative modes, while GANs promote more efficient optimization of SDS.